A Comparison of Health-Related Quality of Life among Normal-Weight, Overweight and Obese Adults in Qazvin Metabolic Diseases Study (QMDS), Iran
Bibliographic record
Abstract
BACKGROUND: Obesity is a public health problem that has raised concern worldwide. Numerous epidemiological studies have been showed the relationship between obesity, abdominal fatness and risk of a wide range of illnesses (i.e. diabetes). Obese people experience health-related quality-of-life (HRQL) impairments. The purpose of this study was to evaluate the effect of BMI on Quality of Life, among Normal-Weight, Overweight and Obese adults in Qazvin, Iran. METHODS: This Cross-Sectional study was conducted on 1103 subjects (aged 20-78 years old) from September 2010 to April 2011 in Qazvin, Iran. The study subjects were selected by multistage cluster random sampling method from residents of mindoodar district of Qazvin. Obesity was defined based on Body Mass Index and SF-36 questionnaire was used as measurement instrument for quality of life. Data were analyzed by Chi-square test, ANOVA and MANOVA. RESULTS: A total of 527 men and 576 women were entered the study. Mean BMI was 25.97 ±4.5 Kg/m2. The scores of 6 domains were significantly different between 3 groups of BMI. The differences of physical component summary (PCS) and mental component summary (MCS) scores were also significant between normal weight, overweight and obese subjects (p<0.001 and p<0.025, respectively). CONCLUSION: This study underlines the importance of HRQL in overweight and obese individuals. These results suggest that more attention to the obesity and overweight is needed in Iranian population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".